Friday, April 21, 2023 From rOpenSci (https://ropensci.org/blog/2023/04/21/ropensci-news-digest-april-2023/). Except where otherwise noted, content on this site is licensed under the CC-BY license.
Dear rOpenSci friends, it’s time for our monthly news roundup!
You can read this post on our blog. Now let’s dive into the activity at and around rOpenSci!
Knowing our community’s stories helps us to learn about the people behind our software, brings us closer and offers us new opportunities. To share some of these community stories, we created the rOpenSci interview series “Meeting the stars of the R-Universe”.
Working with the human brain requires specific software and complex developments. However R appears to be the natural way to collect and analyze the huge amount of data needed, and the R-Universe the most friendly place to share and invite collaborations. Our third stop brings us to Norway to talk with Athanasia Monika Mowinckel. You can also read the post in Spanish.
Have you noticed several of our recent blog posts were translated to Spanish, and in one case, French? We’ve started adding actual multilingual infrastructure to our website. You can find all posts in Spanish in https://ropensci.org/es/archive (and the lone French post in https://ropensci.org/fr/archive). From any post that has a translation, the sidebar on the right (or… at the bottom if you’re reading on mobile!) has a link to translations of the post, see this example.
Over time we plan to further improve the multilingualism of our website.
In previous posts we explained how to create your personal CRAN-like repository and publish packages on R-Universe yourself. A new post explains the other part: how the scraper automatically finds packages on CRAN and Bioconductor to include in the R-Universe.
All in all, R-Universe provides a great way to discover and explore many packages!
We hold Community Calls about every 3 months to share knowledge that is relevant to our community and consistent with our vision and mission. These are free and open for anyone to attend and provide opportunities for us to connect with rOpenSci community members around the world.
We’ve opened an issue in this repository for each topic we’re considering. We’d like your input and “votes” on these, and your suggestions for other topics we haven’t thought of.
We will also be very grateful if you suggest speakers, resources, or encourage others to weigh in by sharing the link to your favorite topic.
We look forward to hearing your ideas. Let’s build the schedule together!
Join us for social coworking & office hours monthly on first Tuesdays! Hosted by Steffi LaZerte and various community hosts. Everyone welcome. No RSVP needed. Consult our Events page to find your local time and how to join.
And remember, you can always cowork independently on work related to R, work on packages that tend to be neglected, or work on what ever you need to get done!
* in the northern hemisphere at least, otherwise, give them a good fall cleaning!
The following three packages recently became a part of our software suite:
concstats, developed by Andreas Schneider: Based on individual market shares of all participants in a market or space, the package offers a set of different structural and concentration measures frequently - and not so frequently - used in research and in practice. Measures can be calculated in groups or individually. The calculated measure or the resulting vector in table format should help practitioners make more informed decisions. It is available on CRAN. It has been reviewed by Sebastian Wojcik, and Christopher T. Kenny.
CRediTas, developed by Josep Pueyo-Ros: A tiny package to generate CRediT author statements (https://credit.niso.org/). It provides three functions: create a template, read it back and generate the CRediT author statement in a text file. It is available on CRAN. It has been reviewed by Marcelo S. Perlin, and João Martins.
predictNMB, developed by Rex Parsons together with Robin Blythe, and Adrian Barnett: Estimates when and where a model-guided treatment strategy may outperform a treat-all or treat-none approach by Monte Carlo simulation and evaluation of the Net Monetary Benefit. Details can be viewed in Parsons et al. (2023) doi:10.21105/joss.05328. It is available on CRAN. It has been reviewed by Emi Tanaka, and Tinula Kariyawasam.
The following nineteen packages have had an update since the last newsletter: commonmark (
v1.9.0), chromer (
v0.4), ckanr (
v0.7.0), concstats (
v0.1.6), CRediTas (
Zenodo_v0.2.0), dbparser (
v2.0.1), dittodb (
v0.1.6), drake (
7.13.5), dynamite (
1.3.2), ezknitr (
v0.6.2), git2r (
v0.32.0), nodbi (
v0.9.2), predictNMB (
v0.1.0), qpdf (
v1.3.2), rgbif (
v3.7.7), rtweet (
v1.2.0), taxizedb (
v0.3.1), tinkr (
0.2.0), and waywiser (
There are thirteen recently closed and active submissions and 2 submissions on hold. Issues are at different stages:
Three at ‘6/approved’:
Three at ‘4/review(s)-in-awaiting-changes’:
Three at ‘3/reviewer(s)-assigned’:
Two at ‘2/seeking-reviewer(s)’:
Two at ‘1/editor-checks’:
Find out more about Software Peer Review and how to get involved.
If you’re interested in maintaining any of the R packages below, you might enjoy reading our blog post What Does It Mean to Maintain a Package? (or listening to its discussion on the R Weekly highlights podcast hosted by Eric Nantz and Mike Thomas)!
rvertnet, Retrieve, map and summarize data from the VertNet.org archives (https://vertnet.org/). Functions allow searching by many parameters, including taxonomic names, places, and dates. In addition, there is an interface for conducting spatially delimited searches, and another for requesting large datasets via email. Issue for volunteering.
citesdb, a high-performance database of shipment-level CITES trade data. Provides convenient access to over 40 years and 20 million records of endangered wildlife trade data from the Convention on International Trade in Endangered Species of Wild Fauna and Flora, stored on a local on-disk, out-of memory ‘DuckDB’ database for bulk analysis. Issue for volunteering.
Refer to our recent blog post to identify other packages where help is especially wished for!
Some useful tips for R package developers. 👀
The R-hub blog has a post on Caching the results of functions of your R package by Maëlle Salmon and Christophe Dervieux. It presents different approaches. A recent PR by Lukas Wallrich to rcrossref maintained by Najko Jahn illustrates the approach of saving results to an environment (and reminded us about the topic of caching!).
If you need to change something like a function or function arguments in your package, you’ll find many resources in, say, the rOpenSci dev guide, or the lifecycle package docs.
Now what if you want to deprecate a dataset?
Read the solution proposed by Matthijs Berends on Stack Overflow, linking to a 3-step method in Bioconductor guidance.
Key is the usage of
delayedAssign() to save a promise that will serve both a warning, and the data.
We might mention this approach in a future version of our dev guide.
You might remember
delayedAssign() from a strategy to provide data as tibble only when tibble is installed.
Andy Teucher, R Package Developer Educator at Posit PBC, wrote a post about “New CRAN requirements for packages with C and C++”. Good to know for packages on CRAN, or to be submitted to CRAN, with compiled code!
Thanks for reading! If you want to get involved with rOpenSci, check out our Contributing Guide that can help direct you to the right place, whether you want to make code contributions, non-code contributions, or contribute in other ways like sharing use cases.